






'''simple docstring'''



def 				lowercase_					(     __A			:							str      )							->   list[int]:



 """simple docstring"""




 lowercase       : List[str]						=[0 for i in range(len(__A      )      )]

 # initialize interval's left pointer and right pointer
 lowercase	,		lowercase       : Any						=0, 0

 for i in range(1       ,   len(__A      )      ):
  # case when current index is inside the interval
  if i <= right_pointer:
   lowercase       : int						=min(right_pointer - i + 1       ,   z_result[i - left_pointer]      )
   lowercase       : Dict						=min_edge

  while go_next(__A       ,   __A       ,   __A      ):
   z_result[i] += 1

  # if new index's result gives us more right interval,
  # we've to update left_pointer and right_pointer
  if i + z_result[i] - 1 > right_pointer:
   lowercase	,		lowercase       : Optional[int]						=i, i + z_result[i] - 1

 return z_result


def 				lowercase_					(     __A			:							int       ,   __A			:							list[int]       ,   __A			:							str      )							->   bool:



 """simple docstring"""




 return i + z_result[i] < len(__A      ) and s[z_result[i]] == s[i + z_result[i]]


def 				lowercase_					(     __A			:							str       ,   __A			:							str      )							->   int:



 """simple docstring"""




 lowercase       : Tuple						=0
 # concatenate 'pattern' and 'input_str' and call z_function
 # with concatenated string
 lowercase       : List[Any]						=z_function(pattern + input_str      )

 for val in z_result:
  # if value is greater then length of the pattern string
  # that means this index is starting position of substring
  # which is equal to pattern string
  if val >= len(__A      ):
   answer += 1

 return answer


if __name__ == "__main__":
      import doctest

      doctest.testmod()











"""simple docstring"""


# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ..models.auto import AutoModelForVisionaSeq
from ..utils import requires_backends
from .base import PipelineTool


if TYPE_CHECKING:
		from PIL import Image




class 						__UpperCamelCase     (     UpperCamelCase						):
					lowercase_    :				Optional[Any]      =  """Salesforce/blip-image-captioning-base"""
					lowercase_    :				Optional[int]      =  (
					    """This is a tool that generates a description of an image. It takes an input named `image` which should be the """
					    """image to caption, and returns a text that contains the description in English."""
					)
					lowercase_    :				int      =  """image_captioner"""
					lowercase_    :				int      =  AutoModelForVisionaSeq

					lowercase_    :				List[str]      =  ["""image"""]
					lowercase_    :				int      =  ["""text"""]
					def __init__(							self							:	Any     , *UpperCAmelCase							:	str     , **UpperCAmelCase							:	List[str]   )	->       Union[str, Any]:
											requires_backends(self     , ['vision']   )
											super().__init__(*UpperCAmelCase     , **UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	int     , UpperCAmelCase							:	"Image"   )	->       Union[str, Any]:
											return self.pre_processor(images=UpperCAmelCase     , return_tensors='pt'   )
					def        UpperCAmelCase__ (							self							:	int     , UpperCAmelCase							:	Optional[int]   )	->       Optional[int]:
											return self.model.generate(**UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	Dict     , UpperCAmelCase							:	int   )	->       Dict:
											return self.pre_processor.batch_decode(UpperCAmelCase     , skip_special_tokens=UpperCAmelCase   )[0].strip()